Detection of clinically significant prostate cancer in biopsy-naïve men: direct comparison of systematic biopsy, multiparametric MRI- and contrast-ultrasound-dispersion imaging-targeted biopsy.

OBJECTIVES: To compare and evaluate a multiparametric magnetic resonance imaging (mpMRI)-targeted biopsy (TBx) strategy, contrast-ultrasound-dispersion imaging (CUDI)-TBx strategy and systematic biopsy (SBx) strategy for the detection of clinically significant prostate cancer (csPCa) in biopsy-naïve men. PATIENTS AND METHODS: A prospective, single-centre paired diagnostic study included 150 biopsy-naïve men, from November 2015 to November 2018. All men underwent pre-biopsy mpMRI and CUDI followed by a 12-core SBx taken by an operator blinded from the imaging results. Men with suspicious lesions on mpMRI and/or CUDI also underwent MRI-TRUS fusion-TBx and/or cognitive CUDI-TBx after SBx by a second operator. A non-inferiority analysis of the mpMRI- and CUDI-TBx strategies in comparison with SBx for International Society of Urological Pathology Grade Group [GG] ≥2 PCa in any core with a non-inferiority margin of 1 percentage point was performed. Additional analyses for GG ≥2 PCa with cribriform growth pattern and/or intraductal carcinoma (CR/IDC), and GG ≥3 PCa were performed. Differences in detection rates were tested using McNemar's test with adjusted Wald confidence intervals. RESULTS: After enrolment of 150 men, an interim analysis was performed. Both the mpMRI- and CUDI-TBx strategies were inferior to SBx for GG ≥2 PCa detection and the study was stopped. SBx found significantly more GG ≥2 PCa: 39% (56/142), as compared with 29% (41/142) and 28% (40/142) for mpMRI-TBx and CUDI-TBx, respectively (P < 0.05). SBx found significantly more GG = 1 PCa: 14% (20/142) compared to 1% (two of 142) and 3% (four of 142) with mpMRI-TBx and CUDI-TBx, respectively (P < 0.05). Detection of GG ≥2 PCa with CR/IDC and GG ≥3 PCa did not differ significantly between the strategies. The mpMRI- and CUDI-TBx strategies were comparable in detection but the mpMRI-TBx strategy had less false-positive findings (18% vs 53%). CONCLUSIONS: In our study in biopsy-naïve men, the mpMRI- and CUDI-TBx strategies had comparable PCa detection rates, but the mpMRI-TBX strategy had the least false-positive findings. Both strategies were inferior to SBx for the detection of GG ≥2 PCa, despite reduced detection of insignificant GG = 1 PCa. Both strategies did not significantly differ from SBx for the detection of GG ≥2 PCa with CR/IDC and GG ≥3 PCa.

Contrast-enhanced ultrasound with dispersion analysis for the localization of prostate cancer: correlation with radical prostatectomy specimens.

PURPOSE: To determine the value of two-dimensional (2D) contrast-enhanced ultrasound (CEUS) imaging and the additional value of contrast ultrasound dispersion imaging (CUDI) for the localization of clinically significant prostate cancer (csPCa). METHODS: In this multicentre study, subjects scheduled for a radical prostatectomy underwent 2D CEUS imaging preoperatively. CUDI maps were generated from the CEUS recordings. Both CEUS recordings and CUDI maps were scored on the likelihood of presenting csPCa (any Gleason ≥ 4 + 3 and Gleason 3 + 4 larger than 0.5 mL) by five observers and compared to radical prostatectomy histopathology. An automated three-dimensional (3D) fusion protocol was used to match imaging with histopathology. Receiver operator curve (ROC) analysis was performed per observer and imaging modality. RESULTS: 133 of 216 (62%) patients were included in the final analysis. Average area under the ROC for all five readers for CEUS, CUDI and the combination was 0.78, 0.79 and 0.78, respectively. This yields a sensitivity and specificity of 81 and 64% for CEUS, 83 and 56% for CUDI and 83 and 55% for the combination. Interobserver agreement for CEUS, CUDI and the combination showed kappa values of 0.20, 0.18 and 0.18 respectively. CONCLUSION: The sensitivity and specificity of 2D CEUS and CUDI for csPCa localization are moderate. Despite compressing CEUS in one image, CUDI showed a similar performance to 2D CEUS. With a sensitivity of 83% at cutoff point 3, it could become a useful imaging procedure, especially with 4D acquisition, improved quantification and combination with other US imaging techniques such as elastography.

Multiparametric Ultrasound for Prostate Cancer Detection and Localization: Correlation of B-mode, Shear Wave Elastography and Contrast Enhanced Ultrasound with Radical Prostatectomy Specimens.

PURPOSE: Similar to multiparametric magnetic resonance imaging, multiparametric ultrasound represents a promising approach to prostate cancer imaging. We determined the diagnostic performance of B-mode, shear wave elastography and contrast enhanced ultrasound with quantification software as well as the combination, multiparametric ultrasound, for clinically significant prostate cancer localization using radical prostatectomy histopathology as the reference standard. MATERIALS AND METHODS: From May 2017 to July 2017, 50 men with biopsy proven prostate cancer underwent multiparametric ultrasound before radical prostatectomy at 1 center. Three readers independently evaluated 12 anatomical regions of interest for the likelihood of clinically significant prostate cancer on a 5-point Likert scale for all separate ultrasound modalities and multiparametric ultrasound. A logistic linear mixed model was used to estimate diagnostic performance for the localization of clinically significant prostate cancer (any tumor with Gleason score 3 + 4 = 7 or greater, tumor volume 0.5 ml or greater, extraprostatic extension or stage pN1) using a Likert score of 3 or greater and 4 or greater as the threshold. To detect the index lesion the readers selected the 2 most suspicious regions of interest. RESULTS: A total of 48 men were included in the final analysis. The region of interest specific sensitivity of multiparametric ultrasound (Likert 3 or greater) for clinically significant prostate cancer was 74% (95% CI 67-80) compared to 55% (95% CI 47-63), 55% (95% CI 47-63) and 59% (95% CI 51-67) for B-mode, shear wave elastography and contrast enhanced ultrasound, respectively. Multiparametric ultrasound sensitivity was significantly higher for Likert thresholds and all different clinically significant prostate cancer definitions (all p <0.05). Multiparametric ultrasound improved the detection of index lesion prostate cancer. CONCLUSIONS: Multiparametric ultrasound of the prostate, consisting of B-mode, shear wave elastography and contrast enhanced ultrasound with parametric maps, improved localization and index lesion detection of clinically significant prostate cancer compared to single ultrasound modalities, yielding good sensitivity.

Multiparametric ultrasound: evaluation of greyscale, shear wave elastography and contrast-enhanced ultrasound for prostate cancer detection and localization in correlation to radical prostatectomy specimens.

BACKGROUND: The diagnostic pathway for prostate cancer (PCa) is advancing towards an imaging-driven approach. Multiparametric magnetic resonance imaging, although increasingly used, has not shown sufficient accuracy to replace biopsy for now. The introduction of new ultrasound (US) modalities, such as quantitative contrast-enhanced US (CEUS) and shear wave elastography (SWE), shows promise but is not evidenced by sufficient high quality studies, especially for the combination of different US modalities. The primary objective of this study is to determine the individual and complementary diagnostic performance of greyscale US (GS), SWE, CEUS and their combination, multiparametric ultrasound (mpUS), for the detection and localization of PCa by comparison with corresponding histopathology. METHODS/DESIGN: In this prospective clinical trial, US imaging consisting of GS, SWE and CEUS with quantitative mapping on 3 prostate imaging planes (base, mid and apex) will be performed in 50 patients with biopsy-proven PCa before planned radical prostatectomy using a clinical ultrasound scanner. All US imaging will be evaluated by US readers, scoring the four quadrants of each imaging plane for the likelihood of significant PCa based on a 1 to 5 Likert Scale. Following resection, PCa tumour foci will be identified, graded and attributed to the imaging-derived quadrants in each prostate plane for all prostatectomy specimens. Primary outcome measure will be the sensitivity, specificity, negative predictive value and positive predictive value of each US modality and mpUS to detect and localize significant PCa evaluated for different Likert Scale thresholds using receiver operating characteristics curve analyses. DISCUSSION: In the evaluation of new PCa imaging modalities, a structured comparison with gold standard radical prostatectomy specimens is essential as first step. This trial is the first to combine the most promising ultrasound modalities into mpUS. It complies with the IDEAL stage 2b recommendations and will be an important step towards the evaluation of mpUS as a possible option for accurate detection and localization of PCa. TRIAL REGISTRATION: The study protocol for multiparametric ultrasound was prospectively registered on Clinicaltrials.gov on 14 March 2017 with the registry name 'Multiparametric Ultrasound-Study for the Detection of Prostate Cancer' and trial registration number NCT03091231.

Multiparametric dynamic contrast-enhanced ultrasound imaging of prostate cancer.

OBJECTIVES: The aim of this study is to improve the accuracy of dynamic contrast-enhanced ultrasound (DCE-US) for prostate cancer (PCa) localization by means of a multiparametric approach. MATERIALS AND METHODS: Thirteen different parameters related to either perfusion or dispersion were extracted pixel-by-pixel from 45 DCE-US recordings in 19 patients referred for radical prostatectomy. Multiparametric maps were retrospectively produced using a Gaussian mixture model algorithm. These were subsequently evaluated on their pixel-wise performance in classifying 43 benign and 42 malignant histopathologically confirmed regions of interest, using a prostate-based leave-one-out procedure. RESULTS: The combination of the spatiotemporal correlation (r), mean transit time (µ), curve skewness (κ), and peak time (PT) yielded an accuracy of 81% ± 11%, which was higher than the best performing single parameters: r (73%), µ (72%), and wash-in time (72%). The negative predictive value increased to 83% ± 16% from 70%, 69% and 67%, respectively. Pixel inclusion based on the confidence level boosted these measures to 90% with half of the pixels excluded, but without disregarding any prostate or region. CONCLUSIONS: Our results suggest multiparametric DCE-US analysis might be a useful diagnostic tool for PCa, possibly supporting future targeting of biopsies or therapy. Application in other types of cancer can also be foreseen. KEY POINTS: • DCE-US can be used to extract both perfusion and dispersion-related parameters. • Multiparametric DCE-US performs better in detecting PCa than single-parametric DCE-US. • Multiparametric DCE-US might become a useful tool for PCa localization.

Dynamic contrast-enhanced ultrasound parametric imaging for the detection of prostate cancer.

OBJECTIVE: To investigate the value of dynamic contrast-enhanced (DCE)-ultrasonography (US) and software-generated parametric maps in predicting biopsy outcome and their potential to reduce the amount of negative biopsy cores. MATERIALS AND METHODS: For 651 prostate biopsy locations (82 consecutive patients) we correlated the interpretation of DCE-US recordings with and without parametric maps with biopsy results. The parametric maps were generated by software which extracts perfusion parameters that differentiate benign from malignant tissue from DCE-US recordings. We performed a stringent analysis (all tumours) and a clinical analysis (clinically significant tumours). We calculated the potential reduction in biopsies (benign on imaging) and the resultant missed positive biopsies (false-negatives). Additionally, we evaluated the performance in terms of sensitivity, specificity negative predictive value (NPV) and positive predictive value (PPV) on a per-prostate level. RESULTS: Based on DCE-US, 470/651 (72.2%) of biopsy locations appeared benign, resulting in 40 false-negatives (8.5%), considering clinically significant tumours only. Including parametric maps, 411/651 (63.1%) of the biopsy locations appeared benign, resulting in 23 false-negatives (5.6%). In the per-prostate clinical analysis, DCE-US classified 38/82 prostates as benign, missing eight diagnoses. Including parametric maps, 31/82 prostates appeared benign, missing three diagnoses. Sensitivity, specificity, PPV and NPV were 73, 58, 50 and 79%, respectively, for DCE-US alone and 91, 56, 57 and 90%, respectively, with parametric maps. CONCLUSION: The interpretation of DCE-US with parametric maps allows good prediction of biopsy outcome. A two-thirds reduction in biopsy cores seems feasible with only a modest decrease in cancer diagnosis.

Is There an Added Value of Quantitative DCE-MRI by Magnetic Resonance Dispersion Imaging for Prostate Cancer Diagnosis?

In this multicenter, retrospective study, we evaluated the added value of magnetic resonance dispersion imaging (MRDI) to standard multiparametric MRI (mpMRI) for PCa detection. The study included 76 patients, including 51 with clinically significant prostate cancer (csPCa), who underwent radical prostatectomy and had an mpMRI including dynamic contrast-enhanced MRI. Two radiologists performed three separate randomized scorings based on mpMRI, MRDI and mpMRI+MRDI. Radical prostatectomy histopathology was used as the reference standard. Imaging and histopathology were both scored according to the Prostate Imaging-Reporting and Data System V2.0 sector map. Sensitivity and specificity for PCa detection were evaluated for mpMRI, MRDI and mpMRI+MRDI. Inter- and intra-observer variability for both radiologists was evaluated using Cohen's Kappa. On a per-patient level, sensitivity for csPCa for radiologist 1 (R1) for mpMRI, MRDI and mpMRI+MRDI was 0.94, 0.82 and 0.94, respectively. For the second radiologist (R2), these were 0.78, 0.94 and 0.96. R1 detected 4% additional csPCa cases using MRDI compared to mpMRI, and R2 detected 20% extra csPCa cases using MRDI. Inter-observer agreement was significant only for MRDI (Cohen's Kappa = 0.4250, p = 0.004). The results of this study show the potential of MRDI to improve inter-observer variability and the detection of csPCa.

The Impact of Omitting Contralateral Systematic Biopsy on the Surgical Planning of Patients with a Unilateral Suspicious Lesion on Magnetic Resonance Imaging Undergoing Robot-assisted Radical Prostatectomy for Prostate Cancer.

Background and objective: A combined approach of magnetic resonance imaging (MRI)-targeted biopsy (TBx) and bilateral systematic biopsy (SBx) is advised in patients who have an increased risk of prostate cancer (PCa). The diagnostic gain of SBx in detecting PCa for treatment planning of patients undergoing robot-assisted radical prostatectomy (RARP) is unknown. This study aims to determine the impact of omitting contralateral SBx on the surgical planning of patients undergoing RARP in terms of nerve-sparing surgery (NSS) and extended pelvic lymph node dissection (ePLND). Methods: Case files from 80 men with biopsy-proven PCa were studied. All men had a unilateral suspicious lesion on MRI, and underwent TBx and bilateral SBx. Case files were presented to five urologists for the surgical planning of RARP. Each case file was presented randomly using two different sets of information: (1) results of TBx + bilateral SBx, and (2) results of TBx + ipsilateral SBx. The urologists assessed whether they would perform NSS and/or ePLND. Key findings and limitations: A change in the surgical plan concerning NSS on the contralateral side was observed in 9.0% (95% confidence interval [CI] 6.4-12.2) of cases. Additionally, the indication for ePLND changed in 5.3% (95% CI 3.3-7.9) of cases. Interobserver agreement based on Fleiss' kappa changed from 0.44 to 0.15 for the indication of NSS and from 0.84 to 0.83 for the indication of ePLND. Conclusions and clinical implications: In our series, the diagnostic information obtained from contralateral SBx has limited impact on the surgical planning of patients with a unilateral suspicious lesion on MRI scheduled to undergo RARP. Patient summary: In patients with one-sided prostate cancer on magnetic resonance imaging, omitting biopsies on the other side rarely changed the surgical plan with respect to nerve-sparing surgery and the indication to perform extended lymph node dissection.

Corrigendum to "Clinical Trial Protocol: Developing an Image Classification Algorithm for Prostate Cancer Diagnosis on Three-dimensional Multiparametric Transrectal Ultrasound" [Eur. Urol. Open Sci. 49 (2023) 32-43].

[This corrects the article DOI: 10.1016/j.euros.2022.12.018.].

Clinical Trial Protocol: Developing an Image Classification Algorithm for Prostate Cancer Diagnosis on Three-dimensional Multiparametric Transrectal Ultrasound.

Introduction and hypothesis: The tendency toward population-based screening programs for prostate cancer (PCa) is expected to increase demand for prebiopsy imaging. This study hypothesizes that a machine learning image classification algorithm for three-dimensional multiparametric transrectal prostate ultrasound (3D mpUS) can detect PCa accurately. Design: This is a phase 2 prospective multicenter diagnostic accuracy study. A total of 715 patients will be included in a period of approximately 2 yr. Patients are eligible in case of suspected PCa for which prostate biopsy is indicated or in case of biopsy-proven PCa for which radical prostatectomy (RP) will be performed. Exclusion criteria are prior treatment for PCa or contraindications for ultrasound contrast agents (UCAs). Protocol overview: Study participants will undergo 3D mpUS, consisting of 3D grayscale, 4D contrast-enhanced ultrasound, and 3D shear wave elastography (SWE). Whole-mount RP histopathology will provide the ground truth to train the image classification algorithm. Patients included prior to prostate biopsy will be used for subsequent preliminary validation. There is a small, anticipated risk for participants associated with the administration of a UCA. Informed consent has to be given prior to study participation, and (serious) adverse events will be reported. Statistical analysis: The primary outcome will be the diagnostic performance of the algorithm for detecting clinically significant PCa (csPCa) on a per-voxel and a per-microregion level. Diagnostic performance will be reported as the area under the receiver operating characteristic curve. Clinically significant PCa is defined as the International Society of Urological grade group ≥2. Full-mount RP histopathology will be used as the reference standard. Secondary outcomes will be sensitivity, specificity, negative predictive value, and positive predictive value for csPCa on a per-patient level, evaluated in patients included prior to prostate biopsy, using biopsy results as the reference standard. A further analysis will be performed on the ability of the algorithm to differentiate between low-, intermediate-, and high-risk tumors. Discussion and summary: This study aims to develop an ultrasound-based imaging modality for PCa detection. Subsequent head-to-head validation trials with magnetic resonance imaging have to be performed in order to determine its role in clinical practice for risk stratification in patients suspected for PCa.

Reliability of whole mount radical prostatectomy histopathology as the ground truth for artificial intelligence assisted prostate imaging.

The development of artificial intelligence-based imaging techniques for prostate cancer (PCa) detection and diagnosis requires a reliable ground truth, which is generally based on histopathology from radical prostatectomy specimens. This study proposes a comprehensive protocol for the annotation of prostatectomy pathology slides. To evaluate the reliability of the protocol, interobserver variability was assessed between five pathologists, who annotated ten radical prostatectomy specimens consisting of 74 whole mount pathology slides. Interobserver variability was assessed for both the localization and grading of PCa. The results indicate excellent overall agreement on the localization of PCa (Gleason pattern ≥ 3) and clinically significant PCa (Gleason pattern ≥ 4), with Dice similarity coefficients (DSC) of 0.91 and 0.88, respectively. On a per-slide level, agreement for primary and secondary Gleason pattern was almost perfect and substantial, with Fleiss Kappa of .819 (95% CI .659-.980) and .726 (95% CI .573-.878), respectively. Agreement on International Society of Urological Pathology Grade Group was evaluated for the index lesions and showed agreement in 70% of cases, with a mean DSC of 0.92 for all index lesions. These findings show that a standardized protocol for prostatectomy pathology annotation provides reliable data on PCa localization and grading, with relatively high levels of interobserver agreement. More complicated tissue characterization, such as the presence of cribriform growth and intraductal carcinoma, remains a source of interobserver variability and should be treated with care when used in ground truth datasets.

Is It the Load That Breaks You or the Way You Carry It: How Demanding Is Endourology?

Objective: Surgical outcomes are dependent on multiple factors. Besides patient-related or procedure-related factors, several surgeon-related factors contribute to surgical outcomes. The Surgery Task Load Index (SURG-TLX) questionnaire helps to assess the impact of several stressors on the perceived demands of surgeons during surgery. In this study, we evaluate the applicability of the SURG-TLX questionnaire for endourologic procedures and set a first point of reference. Materials and Methods: Between March and August 2022, 15 urologists and urology residents at a tertiary referral center for endourology completed the SURG-TLX questionnaire after endourologic procedures. After data acquisition, all participants were asked to evaluate the applicability of the questionnaire for endourologic procedures. Results: A total of 130 procedures were included between March and August 2022. Situational stress had the lowest median score (3.0/20; interquartile range [IQR] 2.0-7.0) and task complexity the highest (5.0/20; IQR 3.0-8.0). After weighing, the dimensions showed different proportions when compared with the nonweighted scores. Distractions received the highest score (15.0/100; IQR 7.5-32.8), temporal demands (6.0/100; IQR 3.0-12.5), and situational stress the lowest (6.0/100; IQR 2.0-21.0). This was caused by the higher weight that was attributed to distractions (3.4/5), as opposed to task complexity (2.6/5). In the questionnaire regarding applicability of the SURG-TLX, the overall satisfaction (6.0/10; IQR 5.0-7.0) and clarity (6.5/10; IQR 5.0-7.5) were moderate. The user-friendliness and applicability of the questionnaire were rated high (7.0/10; IQR 5.5-8.0 and 7.0/10; IQR 6.0-8.0, respectively) and task load (3.0/10; IQR 2.0-5.0) and time load (2.0/10; IQR 2.0-3.5) low. Conclusion: The SURG-TLX questionnaire is appropriate to assess the different dimensions of workload during endourologic procedures. Furthermore, the perceived workload during endourologic procedures is relatively low.

Predictors of clinically significant prostate cancer in biopsy-naïve and prior negative biopsy men with a negative prostate MRI: improving MRI-based screening with a novel risk calculator.

Purpose: A pre-biopsy decision aid is needed to counsel men with a clinical suspicion for clinically significant prostate cancer (csPCa), despite normal prostate magnetic resonance imaging (MRI). Methods: A risk calculator (RC) for csPCa (International Society of Urological Pathology grade group (ISUP) ⩾ 2) presence in men with a negative-MRI (Prostate Imaging-Reporting and Data System (PI-RADS) ⩽ 2) was developed, and its performance was compared with RCs of the European Randomized Study of Screening for Prostate Cancer (ERSPC), Prostate Biopsy Collaborative Group (PBCG), and Prospective Loyola University mpMRI (PLUM). All biopsy-naïve and prior negative biopsy men with a negative-MRI followed by systematic prostate biopsy were included from October 2015 to September 2021. The RC was developed using multivariable logistic regression with the following parameters: age (years), family history of PCa (first- or second-degree family member), ancestry (African Caribbean/other), digital rectal exam (benign/malignant), MRI field strength (1.5/3.0 Tesla), prior negative biopsy status, and prostate-specific antigen (PSA) density (ng/ml/cc). Performance of RCs was compared using receiver operating characteristic (ROC) curve analysis. Results: A total of 232 men were included for analysis, of which 18.1% had csPCa. Parameters associated with csPCa were family history of PCa (p < 0.0001), African Caribbean ancestry (p = 0.005), PSA density (p = 0.002), prior negative biopsy (p = 0.06), and age at biopsy (p = 0.157). The area under the curve (AUC) of the developed RC was 0.76 (95% CI 0.68-0.85). This was significantly better than the RCs of the ERSPC (AUC: 0.59; p = 0.001) and PBCG (AUC: 0.60; p = 0.002), yet similar to PLUM (AUC: 0.69; p = 0.09). Conclusion: The developed RC (Prostate Biopsy Cohort Amsterdam ('PROBA' RC), integrated predictors for csPCa at prostate biopsy in negative-MRI men and outperformed other widely used RCs. These findings require external validation before introduction in daily practice.

An optimized prostate biopsy strategy in patients with a unilateral lesion on prostate magnetic resonance imaging avoids unnecessary biopsies.

Purpose: The introduction of magnetic resonance imaging (MRI)-targeted biopsy (TBx) besides systematic prostate biopsies has resulted in a discussion on what the optimal prostate biopsy strategy is. The ideal template has high sensitivity for clinically significant prostate cancer (csPCa), while reducing the detection rate of clinically insignificant prostate cancer (iPCa). This study evaluates different biopsy strategies in patients with a unilateral prostate MRI lesion. Methods: Retrospective subgroup analysis of a prospectively managed database consisting of patients undergoing prostate biopsy in two academic centres. Patients with a unilateral lesion (PI-RADS ⩾ 3) on MRI were included for analysis. The primary objective was to evaluate the diagnostic performance for different biopsy approaches compared with bilateral systematic prostate biopsy (SBx) and TBx. Detection rates for csPCa (ISUP ⩾ 2), adjusted csPCa (ISUP ⩾ 3) and iPCa (ISUP = 1) were determined for SBx alone, TBx alone, contralateral SBx combined with TBx and ipsilateral SBx combined with TBx. A subgroup analysis was performed for biopsy-naive patients. Results: A total of 228 patients were included from October 2015 to September 2021. Prostate cancer (PCa) detection rate of combined SBx and TBx was 63.5% for csPCa, 35.5% for adjusted csPCa, and 14% for iPCa. The best performing alternative biopsy strategy was TBx and ipsilateral SBx, which reached a sensitivity of 98.6% (95% CI: 95.1-99.6) for csPCa and 98.8% (95% CI: 96.3-99.9) for adjusted csPCa, missing only 1.4% of csPCa, while reducing iPCa detection by 15.6% compared with SBx and TBx. TBx or SBx alone missed a significant amount of csPCa, with sensitivities of 90.3% (95% CI: 84.4-94.2) and 86.8% (95% CI: 80.4-91.4) for csPCa. Subgroup analysis on biopsy-naive patients showed similar results as the overall group. Conclusion: This study shows that performing TBx with ipsilateral SBx and omitting contralateral SBx is the optimal biopsy strategy in patients with a unilateral MRI lesion. With this strategy, a very limited amount of csPCa is missed and iPCa detection is reduced.

Deep Learning for Real-time, Automatic, and Scanner-adapted Prostate (Zone) Segmentation of Transrectal Ultrasound, for Example, Magnetic Resonance Imaging-transrectal Ultrasound Fusion Prostate Biopsy.

BACKGROUND: Although recent advances in multiparametric magnetic resonance imaging (MRI) led to an increase in MRI-transrectal ultrasound (TRUS) fusion prostate biopsies, these are time consuming, laborious, and costly. Introduction of deep-learning approach would improve prostate segmentation. OBJECTIVE: To exploit deep learning to perform automatic, real-time prostate (zone) segmentation on TRUS images from different scanners. DESIGN, SETTING, AND PARTICIPANTS: Three datasets with TRUS images were collected at different institutions, using an iU22 (Philips Healthcare, Bothell, WA, USA), a Pro Focus 2202a (BK Medical), and an Aixplorer (SuperSonic Imagine, Aix-en-Provence, France) ultrasound scanner. The datasets contained 436 images from 181 men. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Manual delineations from an expert panel were used as ground truth. The (zonal) segmentation performance was evaluated in terms of the pixel-wise accuracy, Jaccard index, and Hausdorff distance. RESULTS AND LIMITATIONS: The developed deep-learning approach was demonstrated to significantly improve prostate segmentation compared with a conventional automated technique, reaching median accuracy of 98% (95% confidence interval 95-99%), a Jaccard index of 0.93 (0.80-0.96), and a Hausdorff distance of 3.0 (1.3-8.7) mm. Zonal segmentation yielded pixel-wise accuracy of 97% (95-99%) and 98% (96-99%) for the peripheral and transition zones, respectively. Supervised domain adaptation resulted in retainment of high performance when applied to images from different ultrasound scanners (p > 0.05). Moreover, the algorithm's assessment of its own segmentation performance showed a strong correlation with the actual segmentation performance (Pearson's correlation 0.72, p < 0.001), indicating that possible incorrect segmentations can be identified swiftly. CONCLUSIONS: Fusion-guided prostate biopsies, targeting suspicious lesions on MRI using TRUS are increasingly performed. The requirement for (semi)manual prostate delineation places a substantial burden on clinicians. Deep learning provides a means for fast and accurate (zonal) prostate segmentation of TRUS images that translates to different scanners. PATIENT SUMMARY: Artificial intelligence for automatic delineation of the prostate on ultrasound was shown to be reliable and applicable to different scanners. This method can, for example, be applied to speed up, and possibly improve, guided prostate biopsies using magnetic resonance imaging-transrectal ultrasound fusion.

Contrast-enhanced ultrasound tractography for 3D vascular imaging of the prostate.

Diffusion tensor tractography (DTT) enables visualization of fiber trajectories in soft tissue using magnetic resonance imaging. DTT exploits the anisotropic nature of water diffusion in fibrous structures to identify diffusion pathways by generating streamlines based on the principal diffusion vector. Anomalies in these pathways can be linked to neural deficits. In a different field, contrast-enhanced ultrasound is used to assess anomalies in blood flow with the aim of locating cancer-induced angiogenesis. Like water diffusion, blood flow and transport of contrast agents also shows a principal direction; however, this is now determined by the local vasculature. Here we show how the tractographic techniques developed for magnetic resonance imaging DTT can be translated to contrast-enhanced ultrasound, by first estimating contrast flow velocity fields from contrast-enhanced ultrasound acquisitions, and then applying tractography. We performed 4D in-vivo contrast-enhanced ultrasound of three human prostates, proving the feasibility of the proposed approach with clinically acquired datasets. By comparing the results to histopathology after prostate resection, we observed qualitative agreement between the contrast flow tracts and typical markers of cancer angiogenic microvasculature: higher densities and tortuous geometries in tumor areas. The method can be used in-vivo using a standard contrast-enhanced ultrasound protocol, opening up new possibilities in the area of vascular characterization for cancer diagnostics.

Use of Contrast-Enhanced Ultrasound in the Assessment of Uterine Fibroids: A Feasibility Study.

Contrast-enhanced ultrasound (CEUS) is an innovative ultrasound technique capable of visualizing both the macro- and microvasculature of tissues. In this prospective pilot study, we evaluated the feasibility of using CEUS to visualize the microvasculature of uterine fibroids and compared CEUS with conventional ultrasound. Four women with fibroids underwent gray-scale ultrasound, sonoelastography and power/color Doppler scans followed by CEUS examination. Analysis of CEUS images revealed initial perfusion of the peripheral rim, that is, a pseudo-capsule, followed by enhancement of the entire lesion through vessels traveling from the exterior to the interior of the fibroid. The pseudo-capsules exhibited slight hyper-enhancement, making a clear delineation of the fibroids possible. The centers of three fibroids exhibited areas lacking vascularization, information not obtainable with the other imaging techniques. CEUS is a feasible technique for imaging and quantifying the microvasculature of fibroids. In comparison with conventional ultrasound imaging modalities, CEUS can provide additional diagnostic information based on the microvasculature.

Accurate validation of ultrasound imaging of prostate cancer: a review of challenges in registration of imaging and histopathology.

As the development of modalities for prostate cancer (PCa) imaging advances, the challenge of accurate registration between images and histopathologic ground truth becomes more pressing. Localization of PCa, rather than detection, requires a pixel-to-pixel validation of imaging based on histopathology after radical prostatectomy. Such a registration procedure is challenging for ultrasound modalities; not only the deformations of the prostate after resection have to be taken into account, but also the deformation due to the employed transrectal probe and the mismatch in orientation between imaging planes and pathology slices. In this work, we review the latest techniques to facilitate accurate validation of PCa localization in ultrasound imaging studies and extrapolate a general strategy for implementation of a registration procedure.